Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

def gauss_jordan_elimination(A, B): n = len(B) augmented_matrix = np.hstack([A, B.reshape(-1, 1)]) for i in range(n): # Find the row with the largest pivot element in the current column max_row = i + ...

The dynamic analysis of multibody systems has been significantly advanced through the application of the Transfer Matrix Method (TMM), a robust tool that facilitates the study of complex mechanical ...

This paper presents optimum an one-parameter iteration (OOPI) method and a multi-parameter iteration direct (MPID) method for efficiently solving linear algebraic systems with low order matrix A and ...

For high data rate wireless communications they use Orthogonal Frequency Division Multiplexing (OFDM) due to its high spectral efficiency and low computational complexity. It gives the architecture of ...

Abstract: Recently, analog matrix inversion circuits (INV) have demonstrated significant advantages in solving matrix equations. However, solving large-scale sparse tridiagonal linear systems (TLS) ...

Abstract: In this work, we present a new solution procedure to solve the matrix equation generated by the well-known method of moments (MOM). The first step involves approximating the given structure ...

But still confused about the linear system solver. Is it a direct AMEn procedure [1, algorithm 4] with iteratively updating each tensor-train block of W? (It seems that the linear system in TT-IMP is ...